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Let AI handle
the grind

Tailored workflows for both large and small teams.

Less repetition, higher productivity.

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We design and deploy privacy-first AI systems that run on your infrastructure. Kinoto turns large-scale, messy operational data into well-structured corpora, then trains and evaluates specialized models that solve narrow, high‑value tasks. The result is reliable automation, clear auditability, and full control over data, models, and runtime behavior.

AI is one of the most powerful tools of the century. It builds on decades of research: the internet, social media, big data, hardware advancements, and 30+ years of community knowledge have converged into this remarkable tool. Call it advanced statistics or a search engine on steroids, regardless, it will transform how we live and work as profoundly as the internet itself.

Valentin Radu - Co-founder & Head of product of kinoto.io

Our services

01

Data cleanup and preparation

We gather data from all your sources, remove duplicates, fix inconsistencies, and make it ready for automation.

02

Model training

We train AI models that fit your specific use cases and test them until they behave reliably.

03

Small, focused models

We build smaller, specialized models that do one job extremely well, faster and more accurately.

04

Fine‑tuning for your domain

We teach models your terminology, rules, and preferred output format so results are consistent.

05

Tools and integrations

We connect AI to your systems so it can use APIs, databases, and internal tools safely.

06

Automation in the real world

We integrate AI with physical and digital operations, machines, access systems, and business workflows.

07

Safety and control

We add guardrails and permissions so AI stays predictable and compliant.

08

Orchestration and dashboards

We give you dashboards and workflows (web, app, mobile) to monitor performance and improve over time.

Our approach

A structured methodology that ensures AI works for your team, not against it.

01

Discovery

We start with a conversation to understand your business, identify pain points, and define what success looks like.

02

Team immersion

We meet your people, observe workflows, and build relationships with the teams who will use the system daily.

03

System audit

We map your infrastructure, data sources, and integration points to understand the technical landscape.

04

Needs analysis

We document specific use cases, prioritize by impact, and define measurable success criteria.

05

Hidden conventions

We uncover the unwritten rules, domain terminology, and edge cases that only experienced staff know.

06

Solution design

We architect a system tailored to your context,selecting the right models, planning for privacy and compliance.

07

Environment setup

We prepare your infrastructure, configure data pipelines, and establish security controls.

08

Deployment

We install the AI system with minimal disruption, integrating seamlessly with your existing tools.

09

Training

We educate your team, create documentation, and empower users to get the most from the new system.

10

Validation

We test rigorously in real conditions, validate against success metrics, and iterate based on feedback.

11

Ongoing support

We stay with you,monitoring performance, making adjustments, and answering questions as they arise.

12

Growth

Your AI system evolves with your business,expanding capabilities, improving accuracy, and unlocking new opportunities over time.

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Case study A | Multilingual catalog automation

A large factory needed to generate a 500‑page product catalog in four major languages while keeping content copyright‑safe and consistent. We built a controlled generation pipeline with curated source data, domain‑specific terminology, and automated quality checks.

Result: Over 90% time reduction and ~40% cost reduction with quality preserved.

Case study B | Secure audit intelligence

Our client, a construction audit company, stored measurements, sensor data, and client documents on a private server and struggled with slow, fragmented handoffs. We deployed a secure pipeline that continuously summarizes and aligns audit data across teams, with periodic fine‑tuning for new standards and site‑specific terminology.

Result: Better collaboration, reduced risk, and significant time savings by keeping everyone up to date.